ISMAR 2010
ISMAR 2010 This year’s ISMAR marks its 9th occasion and it seems that mixed and augmented reality technology has finally come of its age, attracting the due attention from the general public. ISMAR 2010 is expected to be not only a great opportunity for the academics and researchers to present and share their latest work in the area, but also provide an impetus for fusing the technology in other areas such as arts, social science, and not to mention lots of business opportunities. In this year ISMAR’s science and technology program published 24 papers, 38 posters, as well as a stimulating mixture of keynote talks, demonstrations, tutorials, workshops and the tracking competition. Out of 107 paper submissions, they have accepted 24 papers, resulting in an overall paper acceptance rate of 22.4%. For this reason, there were several poster and demonstration sessions and also invited all presenters to show their work during breaks whenever they can find the time. Because of the importance of posters in stimulating and communicating novel ideas and applications, ISMAR includes posters in the proceedings as two-page abstracts. Since they have changed their policies this year they don't have a category for the short papers. Therefore few full papers and many posters were there but I felt little bit difficult to understand theories behind those posters because lack of technical details since limited page limit. However, there were few interesting full papers which are relevant to the DSTA projects. Those papers are described below: Positioning, Tracking, and Mapping for Outdoor Navigation This paper is from Interactive Multimedia Lab, Dept. ECE, and National University of Singapore. This presents a novel approach for user positioning, robust tracking and online 3D mapping for outdoor augmented reality applications. As coarse user pose obtained from GPS and orientation sensors is not sufficient for augmented reality applications, sub-meter accurate user pose is then estimated by a one-step silhouette matching approach. Robust visual tracking is maintained by fusing frame-to-frame and model-to-frame feature matches. Frame-to-frame tracking is accomplished with corner matching while edges are used for model-to-frame registration. Results from individual feature tracker are fused using a pose estimate obtained from an extended Kalman filter (EKF) and a weighted M-estimator. The future scope is to increase the robustness of the proposed positioning and mapping approaches. Robust user positioning can be achieved by culling the clutter in the image silhouette, which is associated with unwanted background thereby reducing the number of outliers. Towards Real Time 3D Tracking and Reconstruction on a GPU Using Monte Carlo Simulations This paper is used Bundle Adjustment. Therefore, this might be interesting to DSTA team. This paper addresses the problem of camera tracking and 3D reconstruction from image sequences, i.e., the monocular SLAM problem. This work presents a highly parallelizable random sampling approach based on Monte Carlo simulations that fits very well on the graphics hardware. The proposed algorithm achieves the same precision as non linear optimization, getting real time performance running on commodity graphics hardware. Moreover, results are compared with an implementation of Bundle Adjustment showing that the presented method gets similar results in much less time. This is much faster than PTAM which is very similar to our final application. Augmented Reality in Large Environments: Application to Aided Navigation in Urban Context This paper addresses the challenging issue of vision-based localization in urban context. It briefly describes our contributions in large environments modeling and accurate camera localization. The efficiency of the resulting system is illustrated through Augmented Reality results on large trajectory of several hundred meters. Experimental results illustrate the accuracy of the proposed system through aided navigation scenarios. Further work will devote to on-line SfM drift correction by the aid of coarse 3D city models. This is quite similar to our approach. However, this is a poster so I couldn’t find more details about the details of localization.